Domain experience in Data Analytics jobs - Wyatt Partners

Domain experience in Data Analytics jobs

Frustrations of Data Analytics Leaders

A common frustration of functional Data Analytics Leaders is when they are overlooked for a role by a Company or a Search Firm on the basis that they lack knowledge or experience of working in that sector.

The feeling is that this is an unfair basis on which to judge their suitability for the role, particularly if it prevents them from even getting to the interview process where they can demonstrate their capability in person.

The most common argument is that “Data is Data at the end of the day!”

It’s true that Data is, of course, Data.  But it is also true that not all Data is of equal value and importance to a business, and in many cases, deep domain knowledge or sector familiarity will be a great help in making this judgement.

The Context of any role is important and will inform to a lesser or greater extent the level of domain experience that might be needed.  A simple example being that Data Engineering (Pipelining) roles will not likely need domain experience as long as their is someone in Data Strategy for example who has made the decision on what data to ingest. (That decision could need a lot of domain knowledge).  On the flip side take someone working in a Strategic Analytics team providing insights at Board Level; if they have no knowledge of the domain or the business model, it will be very difficult for them to provide the right analysis & insights the Board are looking for, or even know the right data to be looking at.

Data Analytics Leaders are many things but they are often good at being 2 things:   Translators & Organisers.  Both these things usually require that person to have strong domain expertise.  Let’s examine why:

 

Translators

As a Translator, it’s your job to identify the value AI & Analytics effectively in the business context.  To do that you are going to need to understand the key metrics of that particular business, and how changes in those metrics will likely impact performance on revenue, p&L, customer retention, etc.

If you do not deeply understand these metrics and what change can mean you cannot be an effective translator

 

Organiser

Particularly within large corporates who have access to different kinds of Data and lots of it, one of the major challenges of the Data Analytics leader is to decide where to start in the pursuit of value.  How should you organise your team and on what projects?  Where can you have the quickest wins?  What long term high value projects might you focus on?

Organising your troops in the most optimal way is going to be far easier the more you know about your domain, and the more you understand what are the crucial factors that drive revenue & profits.   This will allow you to have the most impact on the business and in the shortest amount of time possible.

The Exceptions

Sometimes an individual from a different domain can bring crucial experience and different ways of doing things that have huge benefits.  But in most cases, Domain experience means an easy transition and the ability to add value more quickly.  As Data and business have collided in recent years this has never been truer.

 

There is no right or wrong on this as many would try to have you believe, but the narrative that domain experience has no value in the data field is absolutely wrong.  As ever, context is King.

 

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